Known systems utilize image processing techniques where a set of statistical functions are applied to an image (e.g., a satellite image) to generate compensation for band-specific gains. One such technique utilizes statistical analysis to determine where a number of the highest values for each of the bands are selected, and those number of values are treated as being indicative of how the gains of the bands are interrelated. However, such a process of determining gains can result in unintended colored shadows or colored highlights. One such reason for this is that in order for neutral objects to be represented correctly in an image, the digital count values at the spatial location (for each channel) representing neutral objects (e.g. clouds, roads, etc) need to be equivalent (e.g., R=G=B). In known techniques, there are no assurances that pixels treated as neutral are actual neutral objects as seen by the human observer. Also, depending on the linearity of the channel and how sensitive the channel is from an exposure perspective, clipping may occur in the highlight regions or shadow regions, in which the processing in current methods could result in severe coloration in the highlight or shadow regions.